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Record W4200280188 · doi:10.1097/paf.0000000000000739

Loss of Nuclear Basophilic Staining as a Postmortem Interval Marker

2021· article· en· W4200280188 on OpenAlexaff
Samah F. Alabbasi, Ariel C. Viramontes, Francisco J. Díaz, Victor W. Weedn

Bibliographic record

VenueAmerican Journal of Forensic Medicine & Pathology · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForensic Entomology and Diptera Studies
Canadian institutionsOffice of the Chief Medical Examiner
Fundersnot available
KeywordsBasophiliaBasophilicAutopsyPathologyAutolysis (biology)StainingH&E stainHistopathologyMedicineBiology

Abstract

fetched live from OpenAlex

INTRODUCTION: The loss of basophilia (LOB), as an objective marker of postmortem interval (PMI), was evaluated. Such a correlation has been previously reported in stillborn fetuses. METHOD: Loss of basophilia in different tissues was scored using hematoxylin and eosin-stained slides obtained from 65 random autopsy cases. Scatter plots were used to visually assess the correlation of PMI with our LOB scores. Decomposition was assessed using a modified total body score. RESULTS: Loss of basophilia was found to be correlated with PMI (total and unrefrigerated intervals). Specifically in this study, we found full or partial basophilic staining up to 26 hours after death, and complete LOB was seen in cases as early as 36 hours in liver and 60 hours in heart. Loss of basophilia also well correlated with the modified total body score. The LOB varied by tissue and was uncorrelated to histologically observable bacteria and fungi. Refrigeration appeared to stop the autolytic process that causes the LOB. CONCLUSION: Complete LOB can be expected between 1 and 2 days after death in unrefrigerated liver and heart tissues because of autolysis.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.757
Threshold uncertainty score0.821

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.254
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal of Forensic Medicine & PathologySame topicForensic Entomology and Diptera StudiesFrench-language works237,207